Pain management including the use of opioid analgesics is recommended for adolescents who are suffering from recurrent or chronic pain associated with a specific etiology such as cancer, cystic fibrosis, sickle cell anemia, hemophilia or organ transplants (see citations by etiology in letter of support from CO-I, Dr. Solodiuk). Preventive screening tools provide information that can be used by the provider to inform prescription choices (use of opioid versus another medication) and subsequent monitoring (e.g., urine screens, pill counts), resulting in safe and effective pain management. Pediatric hospitals are currently using screeners developed and tested with other populations because there is no validated tool for this specific patient population. The primary aim of this application is to begi development of a screening tool called the Adolescent Screener and Opioid Assessment for Patients with Pain (A-SOAPP) for use with adolescent-aged patients with secondary, recurrent or chronic pain accompanying complex medical conditions like cancer. The A-SOAPP will fill a void that exists for a screening tool to help healthcare providers identify individuals who may be at increased risk for opioid misuse among those patients being considered for episodic or long-term opioid therapy, including cancer patients and patients with sickle cell disease. Similar to development of the adult version, a rigorous methodical approach will be employed to develop a screener with stable, high predictive validity. An adolescent version of such a screener presents significant psychometric challenges including item content that is age-appropriate, accounting for the role of caregivers in the administration and monitoring of medication use, and operationally defining indicators of aberrant medication-related behaviors and signs indicating possible addiction in this population. Thus, in addition to meeting an important clinical need, an age-appropriate, population-appropriate screener for opioid risk represents a significant innovation in the field. In our view, the achievement of this goal will require the concept of a screener to deviate from the self-report behavioral screeners typically used to detect or predict substance use problems. Rather, this screener will endeavor to capitalize on predictive relations of data from a variety of sources (e.g., provider observations, demographic information, medical history, as well as patient self-report), to best model and predict the outcome of interest, namely aberrant medication-related behaviors.